More Causes Less Effect: Destructive Interference in Decision Making
- URL: http://arxiv.org/abs/2106.13320v1
- Date: Sun, 20 Jun 2021 13:34:19 GMT
- Title: More Causes Less Effect: Destructive Interference in Decision Making
- Authors: Irina Basieva, Vijitashwa Pandey, Polina Khrennikova
- Abstract summary: We present a new experiment demonstrating destructive interference in customers' estimates of conditional probabilities of product failure.
We show that when combined, the two causes produce the opposite effect.
Such negative interference of two or more reasons may be exploited for better modeling the cognitive processes taking place in the customers' mind.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present a new experiment demonstrating destructive interference in
customers' estimates of conditional probabilities of product failure. We take
the perspective of a manufacturer of consumer products, and consider two
situations of cause and effect. Whereas individually the effect of the causes
is similar, it is observed that when combined, the two causes produce the
opposite effect. Such negative interference of two or more reasons may be
exploited for better modeling the cognitive processes taking place in the
customers' mind. Doing so can enhance the likelihood that a manufacturer will
be able to design a better product, or a feature within it. Quantum probability
has been used to explain some commonly observed deviations such as question
order and response replicability effects, as well as in explaining paradoxes
such as violations of the sure-thing principle, and Machina and Ellsberg
paradoxes. In this work, we present results from a survey conducted regarding
the effect of multiple observed symptoms on the drivability of a vehicle. We
demonstrate that the set of responses cannot be explained using classical
probability, but quantum formulation easily models it, as it allows for both
positive and negative "interference" between events. Since quantum formulism
also accounts for classical probability's predictions, it serves as a richer
paradigm for modeling decision making behavior in engineering design and
behavioral economics.
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